Recent advances in genomics, molecular biology, and structural biology have highlighted how RNA molecules participate in or control many of the events required to express proteins in cells. Rather than function as simple intermediaries, RNA molecules actively regulate their own transcription from DNA, splice and edit mRNA molecules and tRNA molecules, synthesize peptide bonds in the ribosome, catalyze the migration of nascent proteins to the cell membrane, and provide fine control over the rate of translation of messages. RNA molecules can adopt a variety of unique structural motifs, which provide the framework required to perform these functions.
“Small” molecule therapeutics, which bind specifically to structured RNA molecules, are organic chemical molecules which are not polymers. “Small” molecule therapeutics include the most powerful naturally-occurring antibiotics. For example, the aminoglycoside and macrolide antibiotics are “small” molecules that bind to defined regions in ribosomal RNA (rRNA) structures and work, it is believed, by blocking conformational changes in the RNA required for protein synthesis. Changes in the conformation of RNA molecules have been shown to regulate rates of transcription and translation of mRNA molecules.
An additional opportunity in targeting RNA for drug discovery is that cells frequently create different mRNA molecules in different tissues that can be translated into identical proteins. Processes such as alternative splicing and alternative polyadenylation can create transcripts that are unique or enriched in particular tissues. This provides the opportunity to design drugs that bind to the region of RNA unique in a desired tissue, including tumors, and not affect protein expression in other tissues, or affect protein expression to a lesser extent, providing an additional level of drug specificity generally not achieved by therapeutic targeting of proteins.
RNA molecules or groups of related RNA molecules are believed by Applicants to have regulatory regions that are used by the cell to control synthesis of proteins. The cell is believed to exercise control over both the timing and the amount of protein that is synthesized by direct, specific interactions with mRNA. This notion is inconsistent with the impression obtained by reading the scientific literature on gene regulation, which is highly focused on transcription. The process of RNA maturation, transport, intracellular localization and translation are rich in RNA recognition sites that provide good opportunities for drug binding. Applicants' invention is directed to finding these regions for RNA molecules in the human genome as well as in other animal genomes and prokaryotic genomes.
Combinatorial chemistry is a recent addition to the toolbox of chemists and represents a field of chemistry dealing with the synthesis of a large number of chemical entities. This is generally achieved by condensing a small number of reagents together in all combinations defined by a given reaction sequence. Advances in this area of chemistry include the use of chemical software tools and advanced computer hardware which has made it possible to consider possibilities for synthesis in orders of magnitude greater than the actual synthesis of the library compounds. The concept of “virtual library” is used to indicate a collection of candidate structures that would theoretically result from a combinatorial synthesis involving reactions of interest and reagents to effect those reactions. It is from this virtual library that compounds are selected to be actually synthesized.
Project Library (MDL Information Systems, Inc., San Leandro, Calif.) is said to be a desktop software system which supports combinatorial research efforts. (Practical Guide to Combinatorial Chemistry, A. W. Czarnik and S. H. DeWitt, eds., 1997, ACS, Washington, D.C.) The software is said to include an information-management module for the representation and search of building blocks, individual molecules, complete combinatorial libraries, and mixtures of molecules, and other modules for computational support for tracking mixture and discrete-compound libraries.
Molecular Diversity Manager (Tripos, Inc., St. Louis, Mo.) is said to be a suite of software modules for the creation, selection, and management of compound libraries. (Practical Guide to Combinatorial Chemistry, A. W. Czarnik and S. H. DeWitt, eds., 1997, ACS, Washington, D.C.) The LEGION and SELECTOR modules are said to be useful in creating libraries and characterizing molecules in terms of both 2-dimensional and 3-dimensional structural fingerprints, substituent parameters, topological indices, and physicochemical parameters.
Afferent Systems (San Francisco, Calif.) is said to offer combinatorial library software that creates virtual molecules for a database. It is said to do this by virtually reacting precursor molecules and selecting those that could be actually synthesized (Wilson, C&EN, Apr. 27, 1998, p.32).
While only Project Library and Molecular Diversity Manager are available commercially, these products do not provide facilities to efficiently track reagents and synthesis conditions employed for the introduction of fragments into the desired compounds being generated. Further, these products are unable to track mixtures of compounds that are generated by the introduction of multiple fragments by the use of multiple reagents. Therefore, it is desirable to have available methods for handling mixtures of compounds, as well as methods for the tracking of chemical reactions or transformations utilized in the synthesis of individual compounds and mixtures thereof.
Combinatorial chemistry is a recent addition to the toolbox of chemists and represents a field of chemistry dealing with the synthesis of a large number of chemical entities. This is generally achieved by condensing a small number of reagents together in all combinations defined by a given reaction sequence. Advances in this area of chemistry include the use of chemical software tools and advanced computer hardware which has made it possible to consider possibilities for synthesis in orders of magnitude greater than the actual synthesis of the library compounds. The concept of “virtual library” is used to indicate a collection of candidate structures that would theoretically result from a combinatorial synthesis involving reactions of interest and reagents to effect those reactions. It is from this virtual library that compounds are selected to be actually synthesized.
Project Library (MDL Information Systems, Inc., San Leandro, Calif.) is said to be a desktop software system which supports combinatorial research efforts. (Practical Guide to Combinatorial Chemistry, A. W. Czarnik and S. H. DeWitt, eds., 1997, ACS, Washington, D.C.) The software is said to include an information-management module for the representation and search of building blocks, individual molecules, complete combinatorial libraries, and mixtures of molecules, and other modules for computational support for tracking mixture and discrete-compound libraries.
Molecular Diversity Manager (Tripos, Inc., St. Louis, Mo.) is said to be a suite of software modules for the creation, selection, and management of compound libraries. (Practical Guide to Combinatorial Chemistry, A. W. Czarnik and S. H. DeWitt, eds., 1997, ACS, Washington, D.C.) The LEGION and SELECTOR modules are said to be useful in creating libraries and characterizing molecules in terms of both 2-dimensional and 3-dimensional structural fingerprints, substituent parameters, topological indices, and physicochemical parameters.
Afferent Systems (San Francisco, Calif.) is said to offer combinatorial library software that creates virtual molecules for a database. It is said to do this by virtually reacting precursor molecules and selecting those that could be actually synthesized (Wilson, C&EN, Apr. 27, 1998, p.32).
While only Project Library and Molecular Diversity Manager are available commercially, these products do not provide facilities to efficiently track the reagents employed for the introduction of fragments into the desired compounds being generated. Further, these products are unable to track mixtures of compounds that are generated by the introduction of multiple fragments by the use of multiple reagents. Therefore, it is desirable to have available methods for handling mixtures of compounds, as well as methods for the tracking of chemical reactions or transformations utilized in the synthesis of individual compounds and mixtures thereof.
The selection of compounds for synthesis and screening is a critical step in any drug discovery process. This is particularly true for combinatorial chemistry-based discovery strategies, where a very much larger number of compounds can be conceived than can be prepared in a reasonable time frame. Computational chemistry methods have been applied to find the “best” sets of compounds for screening. One strategy optimizes the chemical “diversity” in a library in order to increase the likelihood of finding a hit with biological activity in a screen against a macromolecular target of unknown structure.
Targeting nucleic acids has been recognized as a valid strategy for interference with biological pathways and the treatment of disease. In this regard, both deoxyribonucleic acids (DNA) and ribonucleic acids (RNA) have been the target of numerous therapeutic strategies. A wide variety of “small” molecules, oligomers and oligonucleotides have been shown to possess binding affinity for nucleic acids. The vast majority of experience in interfering with nucleic acid function has been via the specific binding of ligands to a particular base, base pair, and/or primary sequence of bases in the nucleic acid target. Some compounds have also demonstrated a composite specificity that arises from recognition and interactions with both the primary and secondary structural features of the nucleic acid, such as preferential binding to A-T base pairs in the DNA minor groove, with little or no binding to corresponding RNA sequences.
Exploiting the knowledge of the three-dimensional structure of biological targets is a promising strategy from a drug design and discovery standpoint. This has been demonstrated by the design and development of numerous drugs and drug candidates targeted to proteins involved in various pathophysiological pathways. While three dimensional structures of proteins have been widely determined by techniques such as X-ray crystallography, molecular modeling and NMR, nucleic acid targets have been difficult to study. The literature reveals few three dimensional structures of biologically active RNA, including a tRNA, said to have been determined via X-ray crystallography. Quigley, et al., Nucleic Acids Res., 1975, 2, 2329; and Moras, et al., Nature (London), 1980, 288, 669. The difficulties associated with proper crystallization and study of nucleic acids by X-ray methods along with the increasing number of biologically important small RNAs have increased the need for new structure determination and drug discovery strategies for such targets.
Many approaches to predicting RNA structure have been discussed in the scientific literature. Essentially, these involve sequencing and genomic analysis of nucleic acids, such as RNA, as a first step to establish the primary sequence structure and potential folded structures of the target. A second step entails definition of structural constraints such as base pairing and long range interactions among bases based on information derived from cross-linking, biochemical and genetic structure-function studies. This information, together with modeling and simulation software, has allowed scientists to predict three dimensional models of RNA and DNA. While such models may not be as powerful as X-ray crystal structures, they have been useful in ascertaining some structural features and structure-function relationships.
An understanding of the structural features of specific motifs in nucleic acids, especially hairpins, loops, helices and double helices, has been found to be useful in gaining molecular insights. For example, a hairpin motif comprising a double helical stem and a single-stranded loop is believed to be one of the simplest yet most important structural element in nucleic acids. Such hairpin structures are proposed to be nucleation sites and serve as major building blocks for the folded three dimensional structure of RNAs. Shen, et al., FASEB J., 1995, 9, 1023. Hairpins are also involved in specific interactions with a variety of proteins to regulate gene expression. Feng, et al., Nature, 1988, 334, 165, Witherell, et al., Prog. Nucleic Acid Res. Mol Biol., 1991, 40, 185, and Phillipe, et al., J. Mol. Biol., 1990, 211, 415. Nucleic acid hairpin structures have therefore been widely studied by NMR, molecular modeling techniques such as constrained molecular dynamics and distance geometry (Cheong, et al., Nature, 1990, 346, 680 and Cain, et al., Nuc. Acids Res., 1995, 23, 2153), X-ray crystallography (Valegard, et al., Nature, 1994, 371, 623 and Chattopadhyaya, et al., Nature, 1988, 334, 175), and theoretical methods (Tung, Biophysical J., 1997, 72, 876, Erie, et al., Biopolymers, 1993, 33, 75, and Raghunathan, et al., Biochemistry, 1991, 30, 782.
The determination of potential three dimensional structures of nucleic acids and their attendant structural motifs affords insights into areas such as the study of catalysis by RNA, RNA-RNA interactions, RNA-nucleic acid interactions, RNA-protein interactions, and the recognition of small molecules by nucleic acids. Four general approaches to the generation of model three dimensional structures of RNA have been demonstrated in the literature. All of these employ sophisticated molecular modeling and computational algorithms for the simulation of folding and tertiary interactions within target nucleic acids, such as RNA. Westhof and Altman (Proc. Natl. Acad. Sci., 1994, 91, 5133) have described the generation of a three-dimensional working model of M1 RNA, the catalytic RNA subunit of RNase P from E. coli via an interactive computer modeling protocol. Leveraging the significant body of work in the area of cryo-electron microscopy (cryo-EM) and biochemical studies on ribosomal RNAs, Mueller and Brimacombe (J. Mol. Biol., 1997, 271, 524) have constructed a three dimensional model of E. coli 16S Ribosomal RNA. A method to model nucleic acid hairpin motifs has been developed based on a set of reduced coordinates for describing nucleic acid structures and a sampling algorithm that equilibriates structures using Monte Carlo (MC) simulations (Tung, Biophysical J, 1997, 72, 876, incorporated herein by reference in its entirety). MC-SYM is yet another approach to predicting the three dimensional structure of RNAs using a constraint-satisfaction method. Major, et al., Proc. Natl. Acad. Sci., 1993, 90, 9408. The MC-SYM program is an algorithm based on constraint satisfaction that searches conformational space for all models that satisfy query input constraints, and is described in, for example, Cedergren, et al., RNA Structure And Function, 1998, Cold Spring Harbor Lab. Press, p.37-75. Three dimensional structures of RNA are produced by that method by the stepwise addition of nucleotide having one or several different conformations to a growing oligonucleotide model.
Westhof and Altman (Proc. Natl. Acad. Sci., 1994, 91, 5133) have described the generation of a three-dimensional working model of M1 RNA, the catalytic RNA subunit of RNase P from E. coli via an interactive computer modeling protocol. This modeling protocol incorporated data from chemical and enzymatic protection experiments, phylogenetic analysis, studies of the activities of mutants and the kinetics of reactions catalyzed by the binding of substrate to M1 RNA. Modeling was performed for the most part as described in the literature. Westhof, et al., in “Theoretical Biochemistry and Molecular Biophysics,” Beveridge and Lavery (eds.), Adenine, N.Y., 1990, 399. In general, starting with the primary sequence of M1 RNA, the stem-loop structures and other elements of secondary structure were created. Subsequent assembly of these elements into a three dimensional structure using a computer graphics station and FRODO (Jones, J. Appl. Crystallogr., 1978, 11, 268) followed by refinement using NUCLIN-NUCLSQ afforded a RNA model that had correct geometries, the absence of bad contacts, and appropriate stereochemistry. The model so generated was found to be consistent with a large body of empirical data on M1 RNA and opens the door for hypotheses about the mechanism of action of RNase P. However, the models generated by this method are less well resolved that the structures determined via X-ray crystallography.
Mueller and Brimacombe (J. Mol. Biol., 1997, 271, 524) have constructed a three dimensional model of E. coli 16S ribosomal RNA using a modeling program called ERNA-3D. This program generates three dimensional structures such as A-form RNA helices and single-strand regions via the dynamic docking of single strands to fit electron density obtained from low resolution diffraction data. After helical elements have been defined and positioned in the model, the configurations of the single strand regions is adjusted, so as to satisfy any known biochemical constraints such as RNA-protein cross-linking and foot-printing data.
A method to model nucleic acid hairpin motifs has been developed based on a set of reduced coordinates for describing nucleic acid structures and a sampling algorithm that equilibriates structures using Monte Carlo (MC) simulations. Tung, Biophysical J., 1997, 72, 876, incorporated herein by reference. The stem region of a nucleic acid can be adequately modeled by using a canonical duplex formation. Using a set of reduced coordinates, an algorithm that is capable of generating structures of single stranded loops with a pair of fixed ends was created. This allows efficient structural sampling of the loop in conformational space. Combining this algorithm with a modified Metropolis Monte Carlo algorithm afforded a structure simulation package that simplifies the study of nucleic acid hairpin structures by computational means.
Knowledge and mastery of the foregoing techniques is assumed to be part of the ordinary skill in the art. There has been a long-felt need in the art to provide methods for improved determination of the three-dimensional structure of important regulatory and other elements in nucleic acids, especially RNA. It is also been greatly desired to achieve improved knowledge about the nature of interactions between ligands and potential ligands or nucleic acids, especially RNA. The present invention is directed towards satisfaction of these objectives.
The process of drug discovery is changing at a fast pace because of the rapid progress and evolution of a number of technologies that impact this process. Drug discovery has evolved from what was, several decades ago, essentially random screening of natural products, into a scientific process that not only includes the rational and combinatorial design of large numbers of synthetic molecules as potential bioactive agents, such as ligands, agonists, antagonists, and inhibitors, but also the identification, and mechanistic and structural characterization of their biological targets, which may be polypeptides, proteins, or nucleic acids. These key areas of drug design and structural biology are of tremendous importance to the understanding and treatment of disease. However, significant hurdles need to be overcome when trying to identify or develop high affinity ligands for a particular biological target. These include the difficulty surrounding the task of elucidating the structure of targets and targets to which other molecules may be bound or associated, the large numbers of compounds that need to be screened in order to generate new leads or to optimize existing leads, the need to dissect structural similarities and dissimilarities between these large numbers of compounds, correlating structural features to activity and binding affinity, and the fact that small structural changes can lead to large effects on biological activities of compounds.
Traditionally, drug discovery and optimization have involved the expensive and time-consuming, and therefore slow, process of synthesis and evaluation of single compounds bearing incremental structural changes. When using natural products, the individual components of extracts had to be painstakingly separated into pure constituent compounds prior to biological evaluation. Further, all compounds had to he carefully analyzed and characterized prior to in vitro screening. These screens typically included evaluation of candidate compounds for binding affinity to their target, competition for the ligand binding site, or efficacy at the target as determined via inhibition, cell proliferation, activation or antagonism end points. Considering all these facets of drug design and screening that slow the process of drug discovery, a number of approaches to alleviate or remedy these matters, have been implemented by those involved in discovery efforts.
One way in which the drug discovery process is being accelerated is by the generation of large collections, libraries, or arrays of compounds. The strategy of discovery has moved from selection of drug leads from among compounds that are individually synthesized and tested to the screening of large collections of compounds. These collections may be from natural sources (Sternberg et al., Proc. Natl. Acad. Sci. USA, 1995, 92, 1609-1613) or generated by synthetic methods such as combinatorial chemistry (Ecker and Crooke, Bio/Technology, 1995, 13, 351-360 and U.S. Pat. No. 5,571,902, incorporated herein by reference). These collections of compounds may be generated as libraries of individual, well-characterized compounds synthesized, e.g. via high throughput, parallel synthesis or as a mixture or a pool of up to several hundred or even several thousand molecules synthesized by split-mix or other combinatorial methods. Screening of such combinatorial libraries has usually involved a binding assay to determine the extent of ligand-receptor interaction (Chu et al., J. Am. Chem. Soc., 1996, 118, 7827-35). Often the ligand or the target receptor is immobilized onto a surface such as a polymer bead or plate. Following detection of a binding event, the ligand is released and identified. However, solid phase screening assays can be rendered difficult by non-specific interactions.
Whether screening of combinatorial libraries is performed via solid-phase, solution methods or otherwise, it can be a challenge to identify those components of the library that bind to the target in a rapid and effective manner and which, hence, are of greatest interest. This is a process that needs to be improved to achieve ease and effectiveness in combinatorial and other drug discovery processes. Several approaches to facilitating the understanding of the structure of biopolymeric and other therapeutic targets have also been developed so as to accelerate the process of drug discovery and development. These include the sequencing of proteins and nucleic acids (Smith, in Protein Sequencing Protocols, Humana Press, Totowa, N.J., 1997; Findlay and Geisow, in Protein Sequencing: A Practical Approach, IRL Press, Oxford, 1989; Brown, in DNA Sequencing, IRL Oxford University Press, Oxford, 1994; Adams, Fields and Venter, in Automated DNA Sequencing and Analysis, Academic Press, San Diego, 1994). These also include elucidating the secondary and tertiary structures of such biopolymers via NMR (Jefson, Ann. Rep. in Med. Chem., 1988, 23, 275; Erikson et al., Ann. Rep. in Med. Chem., 1992, 27, 271-289), X-ray crystallography (Erikson et al., Ann. Rep. in Med. Chem., 1992, 27, 271-289) and the use of Computer algorithms to attempt the prediction of protein folding (Copeland, in Methods of Protein Analysis: A Practical Guide to Laboratory Protocols, Chapman and Hall, New York, 1994; Creighton, in Protein Folding, W. H. Freeman and Co., 1992). Experiments such as ELISA (Kemeny and Challacombe, in ELISA and other Solid Phase Immunoassays: Theoretical and Practical Aspects; Wiley, N.Y., 1988) and radioligand binding assays (Berson et al., Clin. Chim. Acta, 1968, 22, 51-60; Chard, in “An Introduction to Radioimmunoassay and Related Techniques,” Elsevier press, Amsterdam/N.Y., 1982), the use of surface-plasmon resonance (Karlsson, Michaelsson and Mattson, J. Immunol. Methods, 1991, 145, 229; Jonsson et al., Biotechniques, 1991, 11, 620), and scintillation proximity assays (Udenfriend et al., Anal. Biochem., 1987, 161, 494-500) are being used to understand the nature of the receptor-ligand interaction.
All of the foregoing paradigms and techniques are now available to persons of ordinary skill in the art and their understanding and mastery is assumed herein.
Likewise, advances have occurred in the chemical synthesis of compounds for high-throughput biological screening. Combinatorial chemistry, computational chemistry, and the synthesis of large collections of mixtures of compounds or of individual compounds have all facilitated the rapid synthesis of large numbers of compounds for ill vitro screening. Despite these advances, the process of drug discovery and optimization entails a sequence of difficult steps. This process can also be an expensive one because of the costs involved at each stage and the need to screen large numbers of individual compounds. Moreover, the structural features of target receptors can be elusive.
One step in the identification of bioactive compounds involves the determination of binding affinity of test compounds for a desired biopolymeric or other receptor, such as a specific protein or nucleic acid combination thereof. For combinatorial chemistry, with its ability to synthesize, or isolate from natural sources, large numbers of compounds for ill vitro biological screening, this challenge is magnified. Since combinatorial chemistry generates large numbers of compounds or natural products, often isolated as mixtures, there is a need for methods which allow rapid determination of those members of the library or mixture that are most active or which bind with the highest affinity to a receptor target.
From a related perspective, there are available to the drug discovery scientist a number of tools and techniques for the structural elucidation of biologically interesting targets, for the determination of the strength and stoichiometry of target-ligand interactions, and for the determination of active components of combinatorial mixtures.
Techniques and instrumentation are available for the sequencing of biological targets such as proteins and nucleic acids (e.g. Smith, in Protein Sequencing Protocols, 1997 and Findlay and Geisow, in Protein Sequencing: A Practical Approach, 1989) cited previously. While these techniques are useful, there are some classes and structures of biopolymeric target that are not susceptible to such sequencing efforts, and, in any event, greater convenience and economy have been sought. Another drawback of present sequencing techniques is their inability to reveal anything more than the primary structure, or sequence, of the target.
While X-ray crystallography is a very powerful technique that can allow for the determination of some secondary and tertiary structure of biopolymeric targets (Erikson et al., Ann. Rep. in Med. Chem., 1992, 27, 271-289), this technique can be an expensive procedure and very difficult to accomplish. Crystallization of biopolymers is extremely challenging, difficult to perform at adequate resolution, and is often considered to be as much an art as a science. Further confounding the utility of X-ray crystal structures in the drug discovery process is the inability of crystallography to reveal insights into the solution-phase, and therefore the biologically relevant, structures of the targets of interest.
Some analysis of the nature and strength of interaction between a ligand (agonist, antagonist, or inhibitor) and its target can be performed by ELISA (Kemeny and Challacombe, in ELISA and other Solid Phase Immunoassays: 1988), radioligand binding assays (Berson et al., Clin. 1968, Chard, in “An Introduction to Radioimmunoassay and Related Techniques,” 1982), surface-plasmon resonance (Karlsson et al., 1991, Jonsson et al., Biotechniques, 1991), or scintillation proximity assays (Udenfriend et al., Anal. Biochem., 1987), all cited previously. Thc radioligand binding assays are typically useful only when assessing the competitive binding of the unknown at the biding site for that of the radioligand and also require the use of radioactivity. The surface-plasmon resonance technique is more straight forward to use, but is also quite costly. Conventional biochemical assays of binding kinetics, and dissociation and association constants are also helpful in elucidating the nature of the target-ligand interactions.
When screening combinatorial mixtures of compounds, the drug discovery scientist will conventionally identify an active pool, deconvolute it into its individual members via resynthesis, and identify the active members via analysis of the discrete compounds. Current techniques and protocols for the study of combinatorial libraries against a variety of biologically relevant targets have many shortcomings. The tedious nature, high cost, multi-step character, and low sensitivity of many of the above-mentioned screening technologies are shortcomings of the currently available tools. Further, available techniques do not always afford the most relevant structural information —the structure of a target in solution, for example. Instead they provide insights into target structures that may only exist in the solid phase. Also, the need for customized reagents and experiments for specific tasks is a challenge for the practice of current drug discovery and screening technologies. Current methods also fail to provide a convenient solution to the need for deconvolution and identification of active members of libraries without having to perform tedious re-syntheses and re-analyses of discrete members of pools or mixtures.
Therefore, methods for the screening and identification of complex chemical libraries especially combinatorial libraries are greatly needed such that one or more of the structures of both the target and ligand, the site of interaction between the target and ligand, and the strength of the target-ligand interaction can be determined. Further, in order to accelerate drug discovery, new methods of screening combinatorial libraries are needed to provide ways for the direct identification of the bioactive members from a mixture and to allow for the screening of multiple biomolecular targets in a single procedure. Straightforward methods that allow selective and controlled cleavage of biopolymers, while also analyzing the various fragments to provide structural information, would be of significant value to those involved in biochemistry and drug discovery and have long been desired. Also, it is preferred that the methods not be restricted to one type of biomolecular target, but instead be applicable to a variety of targets such as nucleic acids, peptides, proteins and oligosaccharides.
Accordingly, it is a principal object of the invention to identify molecular interaction sites in nucleic acids, especially RNA. A further object of the invention is to identify secondary structural elements in RNA which are highly likely to give rise to significant therapeutic, regulatory, or other interactions with “small” molecules and the like. Identification of tissue-enriched unique structures in RNA is another objective of the present invention.
It is another objective of the present invention to provide improved characterization of interactions between RNA and other nucleic acids and ligands or potential ligands therefor.
A further object of the invention is to compare molecular interaction sites of RNA with compounds proposed for interaction therewith.
In accordance with preferred embodiments of the present invention, the comparison of molecular interaction sites of RNA with compounds is achieved through comparison of numerical representations of the three-dimensional structure of the molecular interaction site with the three dimensional structure of the ligands in a fashion such that such interactions can be compared as to quality.
Another object of the present invention is the preparation of hierarchies of ligands ranked or ordered in accordance with in accordance with their ability to interact with molecular interaction sites of RNA and other nucleic acid targets.
Yet another object of the present invention is the establishment of databases of the numerical representations of three-dimensional structures of molecular interaction sites of nucleic acids and three-dimensional structures of libraries of ligands. Such databases libraries provide powerful tools for the elucidation of structure and interactions of molecular interaction sites with potential ligands and predictions thereof.
A principal object of the present invention is to provide novel methods for the determination of the structure of biomolecular targets and ligands that interact with them and to ascertain the nature and sites of such interactions.
A further object of the invention is to determine the structural features of biomolecular targets such as peptides, proteins, oligonucleotides, and nucleic acids such as the primary sequence, the secondary and folded structures of biopolymers, and higher order tertiary and quaternary structures of biomolecules that result from intramolecular and intermolecular interactions.
Yet another object of the invention is to determine the site(s) and nature of interaction between a biomolecular target aid a binding ligand or ligands. The binding ligand may be a “small” molecule, a biomolecule such as a peptide, oligonucleotide or oligosaccharide, a natural product, or a member of a combinatorial library.
A further object of the invention is to determine the relative binding affinity or dissociation constant of ligands that bind to biopolymer targets. Preferably, this gives rise to a determination of relative binding affinities between a biopolymer such as an RNA/DNA target and ligands e.g. members of combinatorially synthesized libraries.
A further object of the invention is to determine the absolute binding affinity or dissociation constant of ligands that bind to biopolymer targets.
A still further object of the present invention is to provide a general method for the screening of combinatorial libraries comprising individual compounds or mixtures of compounds against a biomolecular target such as a nucleic acid, so as to determine which components of the library bind to the target.
An additional object of the present invention is to provide methods for the determination of the molecular weight and structure of those members of a combinatorial library that bind to a biomolecular target.
Yet another object of the invention is to provide methods for screening multiple targets such as nucleic acids, proteins, and other biomolecules and oligomers simultaneously against a combinatorial library of compounds.
A still further object of the invention is to ascertain the specificity and affinity of compounds, especially “small” organic molecules to bind to or interact with molecular interaction sites of biological molecules, especially nucleic acids such as RNA. Such molecules may be and preferably do form ranked hierarchies of ligands and potential ligands for the molecular interaction sites, ranked in accordance with predicted or calculated likelihood of interaction with such sites.
Another object of the present invention is to alleviate the problem of peak overlap in mass spectra generated from the analysis of mixtures of screening targets and combinatorial or other mixtures of compounds. In a preferred embodiment, the invention provides methods to solve the problems of mass redundancy in combinatorial or other mixtures of compounds, and also provides methods to solve the problem of mass redundancy in the mixture of targets being screened.
A further object of the invention is to provide methods for determining the binding specificity of a ligand for a target in comparison to a control. The present invention facilitates the determination of selectivity, the identification of non-specific effects and the elimination of non-specific ligands from further consideration for drug discovery efforts.